1. Field of the Invention
The world is comprised of many types of complex ecosystems. However trying to define, navigate and optimize aspects of them remains a difficult challenge. The focus of this invention is: (i) a novel generic framework for describing, analyzing and delineating ecosystems, and (ii) a system, method and unique device aiding decision making among processes and process interdependencies that ‘that matter most’ for optimal ecosystem functioning. While the invention applies to all ecosystems however the (business) enterprise ecosystem is used to illustrate embodiments.
There is a wide range of ecosystems—from large atmospheric, oceanographic and terrestrial systems—to all sizes of physical, chemical, biological and enterprise systems. There is a myriad of representations and models in the prior art, and despite some commonalities, there is little in the way of standard methods that assist navigation and management of these complex systems. This invention addresses complexity to resolve several of the current deficiencies.
All ecosystems and systems are comprised of processes that convert inputs to outputs. This is a ‘process-centric’ perspective. While some supply chain and logistics chain processes are well understood in business enterprises, few standard definitions exist for most processes, process components, relationships and dynamics. This deficiency has constrained development of common process models and development of ‘interoperable’ applications for sharing services via service-orientated architectures (SOA) in federations of enterprises.
Understanding processes requires some abstract thinking and an ability to deal with intangible relationships and concepts, something that does not come easy to many of us. Determining cause/effect relationships is challenging. Processes involve a complex myriad of interactions with multiple non-linear feedback loops, flows and interdependencies. As a result there has been limited emphasis on developing standard process knowledgebase's.
Process knowledge is distinct from data and knowledgebase's are distinct from databases, the latter representing only one state of a process at any given place or time. Process knowledge is required to model cause/effect relationships needed to predict outcomes and ecosystem dynamics.
Sets of 2 or 3 process variables may be illustrated at a single time in 2D (planar) or 3D representations. But ecosystem complexity is much greater than this, often involving in the range of 12 or more process variables (i.e. ‘N=12’ dimensions), each having in the order of 4-6 or more states. Possible combinations and permutations of these may exceed several billion potential state options.
Several methods in the prior art attempt to address the complexity via (i) reusable ‘loosely coupled building block’ objects, (ii) ‘object oriented’ (OO) methods, and (iii) a ‘simple iterative partitions’ (SIP) method of grouping variables. For example, twelve variables each with 6 states produce over 126 or 2 billion state options. However if the variables are partitioned into 2 sets of 6 variables, each having 46,656 states, then there are only 93,312 total states, reducing the complexity by more than 99% without removing any of the variables.
For executive decision-making in enterprise ecosystems, the complexity must be reduced to only a few options. In addition to these, this invention also incorporates: (i) a generic ontology (ii) a hierarchy of generic process operands, (iii) major models and methods in the prior art, and (iv) knowledge acquisition via ‘wiki’ internet collaboration. Taken together, these six methods—OO, SIP, ontology, generic hierarchy, model alignment and wiki—provide a unique system, method and device for navigating complexity to aid ‘informed’ decision-making.
For example, the human body system (skeletal) architecture has 12 major systems—pulmonary, cardiac, endocrine etc. Each has a ‘nested set’ hierarchy of organs, tissues, cells, and proteins—one within the next. Within each of these there is a ‘nested set’ hierarchy of processes, process operands and states that may be characterized.
Similarly enterprise (business) architecture is a hierarchy of 3 major operands—management; demand/supply and implementation processes. Each has 4 processes for a total of 12 processes in all, each with a hierarchy of process operands and states just as in the first example.
These hierarchies may be readily partitioned as we drill down into process and sub-process detail—a structure common in most ecosystems. This facilitates simplification of complexity and navigation of system composition, interactions and flows. Simplification is also aided by aligning prior art models: (i) business process enterprise architecture (EA) models, (ii) process operation reference models (ORM) and (iii) process maturity models (MM). While each model provides some common perspectives, it rarely provides an integrated perspective of the overall system.
The challenge is similar to that described in the poem—Six Blind Men and the Elephant—by John Saxe. Each blind man touched and described a different portion of an elephant (ecosystem)—the ear, tusk, tail, leg, side, and trunk—and all described a different view and perception of an elephant. All were right in one respect, but all were wrong in characterizing the overall elephant ecosystem. Most models in the literature suffer similarly.
This invention aligns these EA, ORM and MM models in the prior art into one. It defines ecosystems with a single generic structure characterized by 12 operands, 6 of which are generic to any system and 6 of which are process specific. One generic operand describes maturity with six generic states.
Key process operand states ‘that matter most’ characterize priority objectives. Selections of only a few key states or many states will define key decision ‘threads’ that may aid process optimization, and/or process interdependency tradeoff decision making. Selection of decision threads linking only the most influential operand states within the hierarchy simplifies complexity and provides focus.
2. Examples of Prior Art
Enterprise architecture reference models in the prior art include the Zachman framework, The Open Group Architecture Framework (TOGAF) the Department of Defense Architecture Framework (DODAF) FEAF; MDA; ARIS and the Service-oriented architecture reference model (SOA/RM). U.S. Pat. No. 7,020,697 1 dated Mar. 28, 2006 by Goodman et al describes an enterprise architecture for net centric computing systems; and US Patent Application Publication US 2006/0136275 A1 dated Jun. 22, 2006 by Cotora describes a method and device for optimizing company structure.
Business process architecture operations reference models include the Supply Chain Council operations reference model (SCOR), the Value Chain Group value reference model (VRM), the Federated Enterprise Reference Architecture (FERA), the Intel Integrated Process and Technology Framework (IPTF) and the American Productivity and Quality Council Process Classification Framework (APQC/PCF). US patent Application Publication US 2007/0038490 A1 dated Feb. 15, 2007 by Joodi describes a method and system for analyzing business architecture; and US Patent Application US 2007/0022404 A1 dated Jan. 25, 2007 by Zhang et al describes a process profiling framework.
Examples of maturity methods include US Patent Application Publication US 2007/0021967 A1 by Jaligama related to the concept of measuring and mapping process maturity levels; US Patent Application Publication US 2005/0159965 A1 of Mann et al describes measurement groups; US Patent Application 2006/0136275 A1 of Cotora describes internal and external value production; U.S. Pat. No. 7,136,792 B2 of Baltz et al describes subjective scoring systems; and US Patent Application US 2007/0027734 dated Feb. 1, 2007 of Hughes describes an enterprise design solution methodology for increasing the maturity level of value chains. There are also maturity methods applied by PRTM Inc., AMR Research Inc., the US Productivity Council and GPT Management Ltd. for innovative capacity as described in U.S. Provisional Patent Applications 60/774,597 Feb. 21, 2006 and 11/676,305 Feb. 18, 2007 by Cornford.
Methods for assessing process value chains, process interdependences and types of value grid relationships include U.S. Pat. No. 7,206,751 B2 dated April 2007 by Hack et al for a value chain optimization system; U.S. Pat. No. 7,231,400 dated Jun. 12, 2007 by Cameron et al for hierarchies of inter-object relationships based on object attribute values; US Patent Application Publication US 2005/0165822 dated Jul. 28, 2005 by Yeung et al for systems and methods for business process automation, analysis and optimization; US Patent Application Publication US 2005/0159965 dated Jul. 21, 2005 by Mann et al for business analysis and management systems utilizing enterprise metrics; and US Patent Publication Application US 2002/0184067 dated Dec. 5, 2002 by McLean et al which describes a method for measuring and reporting on value creation performance that supports real-time benchmarking.
Methods of enterprise value assessment include work by A. Lemus (Johnson and Johnson ASP): Metrics for Monitoring New Product Development, 2003; A. Lemus (Ameriquest Mortgage Co.): Change Management in New Product Development (‘Making it Work’), 2004; D. Hofman (AMR Research Inc.): ‘The Hierarchy of Supply Chain Metrics, Supply Chain Management Review Sep. 1, 2004; D. Hofman and J. Hagerty (AMR Research Inc.): Defining a Measurement Strategy Part I, BI Review Magazine, Mar. 1, 2006; Part II, May 1, 2006; Part III, August 2006; K. Frits and M. Holweg: Evolving from the Value Chain to Value Grid, MIT Sloan Management Review, Summer 2006, No 1.47, No. 4 pp. 72-79, Reprint 47414; A. Cornford, edited by R. Lipsey (Atlantic Canada Opportunities Agency): Benchmarking Innovative Capacity: Policy and Practice 2005; and Innovate America (US Council on Competitiveness): National Innovation Initiative and Summit Report 2004, ISBN 1-889866-20-2; publications of IDS Scheer related to business process management (BPM) and Gartner Inc. including ‘The Gartner Business Value Model: A Framework for Measuring Business performance’, May 31, 2006; ID 600139413.
The prior art describes the use of ‘loosely coupled’ ‘building blocks’ and ‘component business models’ as a basis for defining modular architectures, processes and process service components for service-oriented architectures. These include G. Pohle, P. Korsten and S. Ramamurthy, 2005 (IBM Business Consulting Services): Component Business Models—Making Specialization Real; P. Salz (Accenture): A Modular Approach, 2006; D. Frankel (SAP): A Convergence of Business and IT Thinking”: SOA and the Business-IT Divide, MDA (Model Drive Architecture) Journal January 2007; and B. Jaruzleski, K. Dehoff and R. Bordia (Booz, Allen, Hamilton): Smart Spenders: The Global Innovation 1000, S&B 06405, November 2006; and Cornford, U.S. patent application Ser. No. 12/344,350 relating to ecosystem value stream optimization system, method and device.
3. Introduction
This invention defines complex ecosystem structure in terms of a generic framework architecture and process ontology. It defines a system, method and device that assist transparent navigation of processes that convert inputs to outputs for optimizing ecosystem performance. To date there is no standard set of accepted ontology, architecture, process or process operand definitions for the enterprise in the prior art. This invention provides these as a sound basis for standardization. They include: (i) 3 major process (business) architecture operands; (ii) 6 generic process (ecosystem independent) operands; (iii) 6 process specific operands; (iv) 5 process organizational level (SPEAT) operands; (v) tradeoff operands; and (vi) decision operands. Each of these operand sets may be created used or copied by a set of ‘function’ editors that may access knowedgebase and database directories and files locally and remotely via the internet and wiki protocols.
Enterprise architecture, and specifically business (process) architecture may be described by three architecture operands. These define 3 major categories of processes in the process hierarchy,—‘strategic’ (management) processes, defining core process competencies and guiding ‘core’ (demand/supply) processes, which are delivered by balancing resources within ‘support’ (implementation) processes.
Each of the 3 architecture operands has four operand states which define the four management, four demand/supply and the four implementation processes. For each of these there is a ‘nested set’ hierarchy of 12 generic process attribute operands common in all ecosystems. Each operand generally has in the order of 4-6 states which often then have sub-states and so on.
Six of the process operands and their states are common to all processes. The other six are process specific and characterize a particular system or domain. Each of these process specific operands states may then be further defined in terms of process levels by a suite of process level sub-operands and their states.
Some or all of the 12 operand states may be linked via knowledge ‘threads’ through ecosystems at all levels of aggregation—federations of systems, systems, processes—in all kinds of management, physical, chemical and biological systems.
These threads may include only a few key operand states ‘that matter most’ for driving process value streams via a few value pathways that permit assessment of process interdependencies and tradeoffs. To date there has been no common (enterprise) ecosystem framework structure or ontology in the prior art to accomplish this. This absence has severely limited the ability to assess process interdependencies and development of key performance indicators for process interdependencies that drive most value.
This invention addresses and resolves this need. It aligns and integrates ontology, architecture structure, process structure, process operands, operand states and decision threads within a single, transparent, unified system, method and device. Together these permit transparent assessment of process value outputs, interdependencies guiding tradeoff decisions that may most influence ecosystem overall value. It integrates most major models and methods for architecture, process and maturity in the prior art and has potential to become a standard ecosystem operations reference framework.